glowrs

The glowrs library provides an easy and familiar interface to use pre-trained models for embeddings and sentence similarity.

Example

use glowrs::SentenceTransformer;

fn main() {
    let encoder = SentenceTransformer::from_repo_string("sentence-transformers/all-MiniLM-L6-v2").unwrap();

    let sentences = vec![
        "Hello, how are you?",
        "Hey, how are you doing?"
    ];

    let embeddings = encoder.encode_batch(sentences, true).unwrap();

    println!("{:?}", embeddings);
}

Features

• Load models from Hugging Face Hub
• More to come!

Build features

• metal: Compile with Metal acceleration
• cuda: Compile with CUDA acceleration
• accelerate: Compile with Accelerate framework acceleration (CPU)

Disclaimer

This is still a work-in-progress. The embedding performance is decent but can probably do with some benchmarking.

Do not use this in a production environment.